The reading of electrical energy has historically been accomplished with human meter readers that came on-site to the customers' premises and manually documented the readings. Over time, manual meter reading has been enhanced with walk-by or drive-by reading systems that utilize radio communications between the meters and a meter reading device. The information that these walk-by and drive-by systems collected increased, but still the functions provided by the communication systems were limited.
More recently, over the last few years, there has been a concerted effort to automate meter reading by installing fixed networks that allow data to flow from the meter to a host computer system without human intervention, such systems have been referred to in the art as Automated Meter Reading (AMR) systems. AMR systems have gained interest because there are approximately 150 million installed meters, of which 17 million are considered to be "hard-to-read" because of location, etc. A limitation in these conventional AMR systems is that they typically use only one type of communication infrastructure to gather data. For example, the AMR system may receive data from meters via one of a fixed proprietary RF communications infrastructure, the public switched telephone network or power line transmission. This one-infrastructure communication of data has led to the development of incompatible AMR systems that are tied to that particular communications infrastructure, utilize proprietary devices and protocols, and have unacceptably low data rates. Such implementations are also lacking because RF coverage is limited, and public switched telephone network and power line transmission solutions require relatively long periods of time to communicate data from the meter.
In addition to the limitations regarding communication infrastructures, conventional AMR systems are not easily adaptable to changing requirements of both the energy provider and the energy consumer. For example, while most meters measure energy monthly in kWh or Time-of-Use (TOU), rising consumer demand for daily reads of kWh or TOU, load profile metering along with demand, outage, power quality and tamper monitoring capabilities will render conventional systems obsolete. For example, conventional AMR systems collect data via a pulsed input, and over a period of time to determine energy usage or may create a load profile. These systems, however, are not capable of reading data from newly developing intelligent meters that provide load profile information and the like to the AMR system.
A further limitation of the conventional AMR system is that they do not accommodate the requirements of end-user systems (e.g., billing systems, energy management systems and supervisory control systems). Theses systems are typically standalone systems, separate from the metering system. One of the primary reasons that the requirements of end-user systems are not met is because of the above-mentioned limitations that conventional AMR systems were designed as proprietary systems rather than open systems. These systems generally output the meter data in a raw format that is not compatible with the end-user systems and that must be converted for use. Thus, conventional AMR systems do not perform validation, editing and estimation of the output data, and require a relatively high amount of manual intervention to transfer data from the AMR system to end users for further processing.
Yet another limitation of conventional AMR systems is that metering data has been captured and managed using traditional mainframe or two-tiered client/server architectures. While mainframe and client/server solutions have been up to the present relatively successful in addressing the needs of utilities and their customers, AMR Systems are becoming far too large and complex for conventional technologies because of the amount of data flowing in and out of the system (e.g., it may be necessary to store and process data from daily or hourly meter reads from millions of meters). As data requirements steadily increase in an automated meter reading system, traditional mainframe and two-tiered architectures (non-distributed systems) experience limitations in memory, CPU capabilities, and storage capacity because a growing amount of data traffic over the network leads to bottlenecks that result in performance limitations as data is shipped between the database and the client, and records in the database can become locked when client programs need to lock data to use it. Upgrading these systems to increase the load capability and performance requires bringing the system down. In addition, the cost of maintenance and upgrade of these systems increases as companies attempt to solve client/server performance problems and scalability issues by purchasing bigger and faster machines.
In addition to limitations noted-above in conventional AMR systems, perhaps the greatest limitation of the existing AMR systems is that the electric utility marketplace is moving towards deregulation. Under deregulation, utility customers will be able to choose their electric service providers. As a result, the deregulated marketplace has created many new business entities, which will place additional demands on AMR systems. For example, in California, a Meter Data Management Agent (MDMA) has been created which is responsible for collecting and publishing the data required for billing. Further, the MDMA requires that settlement quality data be provided as the MDMA publishes data to multiple business entities, including the ESP, the UDC and potentially other ancillary services (e.g., third party billing companies, etc.). However, conventional AMR systems were not designed to accommodate the demands of a deregulated market place nor do they provide such capabilities. Further, conventional AMR systems do not accommodate the needs of commercial and industrial (C&I) and residential customers who are interested in determining usage statistics.
Specific examples of conventional AMR and AMR-type systems are described in the prior art. U.S. Pat. No. 5,602,744, to Meek et al., entitled "Universal Send/Receive Utility Usage Data Gathering System", which discloses a universal utility usage data gathering system that can respond and transmit recorded utility consumption to readers manufactured by other vendors. A "buried" emulated protocol responds to another vendor's interrogation pulse and tricks the other vendor's reader into thinking that it is communicating with one of its own meters. The interrogator and the data gathering system may communicate in a synchronous or asynchronous manner depending on the vendor's implementation.
U.S. Pat. No. 5,553,094, to Johnson et al., entitled, "Radio Communication Network for Remote Data Generating Stations", discloses a wide area communications network that collects data generated by a plurality of electric meters for transmission to a central data terminal. Information is transmitted from network service modules to remote cell nodes, which then transfer the information to a central data terminal via intermediate data terminals. The network service modules transmit data packets over RF transmission links to the remote cell nodes located at approximately 0.5 mile intervals, for example, on utility poles or a building. The remote cell nodes periodically forward information via RF transmission links to the intermediate data terminals. The intermediate data terminals are located at 4 mile intervals. The intermediate data terminals communicate to the central data terminal via various different types of links including telephone lines, Ti carriers, fiber optic channels, coaxial cables, microwave, or satellite.
U.S. Pat. No. 5,590,179, to Shincovich et al., entitled "Remote Automatic Meter Reading Apparatus" discloses an adaptor to provide automatic meter reading of conventional watthour meters without requiring modifications to the meters or the socket to which the meters are mounted. The adaptor is interconnected between the meter and the internal telephone communications circuitry. During a predefined transmission wind controller in the adaptor changes modes such that the adaptor may be contacted via telephone to send data to a central utility site.
Also known are distributed networks for communicating data from devices having dissimilar formats and/or protocols. U.S. Pat. No. 5,619,685, to Schiavone, entitled "Run-Time Dynamically Adaptive Computer Process for Facilitating Communication between Computer Programs" discloses a system whereby two dissimilar software programs may communicate with each other on a distributed network by mapping input and output blocks of memory.
In addition to the above system, there are specific examples of AMR products in use. A first is MV-90, which is a product sold by Itron/UTS. While MV-90 supports multiple electric meter manufacturer protocols, as well as several gas meters, gathers load profile, time-of-use, consumption and demand data, and performs some form of meter data validation and issues alerts/alarms, the MV-90 interfaces only to a corresponding proprietary billing system (i.e., the MV-PBS Power Billing System). A further limitation is that MV-90 is a DOS-based AMR system, and therefore is small scale solution and is not scalable to accommodate large scale entities. In addition, MV-90 is limited to communicating with meters via a single telephone modem interface, therefore is considered only a tactical solution for many energy service providers. Still further, MV-90 has not been designed to accommodate and support multiple deregulated business entities and specific regulatory agency validation and estimation schemes.
An example of another AMR product is MAPS, which is offered by Schlumberger. MAPS is a client-server, UNIX-based AMR system that collects data from water, gas and electric meters. The MAPS host software provides scheduling, network management, access to usage and load profile information, and analysis of power usage. Usage information may be shared with other systems such as billing. While MAPS may be more robust than MV-90, it too is limited by the number of meter end points from which information may be collected. Further, there are no data validation or estimation schemes, and MAPS will not accommodate multiple market entities.
In view of the limitations of conventional AMR and AMR-type systems, the AMR system of the present invention addresses the needs and limitations of known systems by providing an end-to-end system that combines communications, data warehousing, processing and consolidation as well as presentation and standard application interface options. In particular, the present invention provides an all-inclusive, highly automated solution by providing an integrated system that is capable of receiving data from a plurality of dissimilar metering devices and communications networks, managing the data, and communicating the data to a plurality of applications and end user systems. The AMR system of the present invention is adapted to communicate with legacy systems and other proprietary systems to provide a total AMR solution not found anywhere in the prior art. The AMR system addresses the need for diverse communication technologies resulting from the relationship of RF coverage to population density (e.g., rural areas may utilize telephone implemented solutions due to very low population density, whereas urban areas are more likely to utilize RF solutions). The AMR system of the present invention addresses the needs of energy providers allowing them to meet the consumer expectations and demands and more effectively compete in an industry that is presently being deregulated to encourage increasing competition.